A Trust-Aware Framework for Reliable Content Dissemination in NDN-Based VANETs Using Hidden Markov Models

Vehicular Ad Hoc Networks (VANETs) play a vital role in intelligent transportation systems where dissemination of trustworthy information is very crucial. Existing trust management schemes and cryptographic techniques in VANET are computationally expensive, which increases latency. To ensure trusted content dissemination in the VANET, the proposed work combines Named Data Networking (NDN) with the Hidden Markov Model (HMM). In NDN, content is searched based on content name rather than IP address which eliminates the need for centralized servers and reduces the latency. HMM is employed to model trustworthiness and improve the authenticity of the content. The Trust-Aware Framework for Reliable Content Dissemination (TAFRCD) consists of four phases, such as trust modeling, trust establishment, trust-based content dissemination, and performance evaluation. Extensive simulation is conducted to assess the efficiency of this strategy by comparing it with existing approaches like NOTRINO and TROVE in terms of trust detection accuracy, content retrieval latency, network overhead, and dissemination efficiency. The results reveal that TAFRCD ensures trustworthy communication in VANET better than existing content distribution and trust management schemes.